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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">finance</journal-id><journal-title-group><journal-title xml:lang="ru">Финансы: теория и практика/Finance: Theory and Practice</journal-title><trans-title-group xml:lang="en"><trans-title>Finance: Theory and Practice</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2587-5671</issn><issn pub-type="epub">2587-7089</issn><publisher><publisher-name>Financial University under The Government of Russian Federation</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26794/2587-5671-2021-25-4-136-151</article-id><article-id custom-type="elpub" pub-id-type="custom">finance-1283</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ЦИФРОВЫЕ ФИНАНСОВЫЕ АКТИВЫ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>DIGITAL FINANCIAL ASSETS</subject></subj-group></article-categories><title-group><article-title>Индекс финансового страха на рынке цифровых финансовых активов</article-title><trans-title-group xml:lang="en"><trans-title>Financial Fear Index in the Digital Financial Assets Market</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-4921-7780</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Овчаров</surname><given-names>А. О.</given-names></name><name name-style="western" xml:lang="en"><surname>Ovcharov</surname><given-names>A. О.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Антон Олегович Овчаров — доктор экономических наук, профессор кафедры бухгалтерского учета</p><p>Нижний Новгород</p></bio><bio xml:lang="en"><p>Anton O. Ovcharov — Dr. Sci. (Econ.), Prof., Department of Accounting</p><p>Nizhny Novgorod,</p><p> </p></bio><email xlink:type="simple">anton19742006@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-9323-2414</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Матвеев</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Matveev</surname><given-names>V. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Виктор Александрович Матвеев — кандидат экономических наук, доцент кафедры бухгалтерского учета</p><p>Нижний Новгород</p></bio><bio xml:lang="en"><p>Viktor A. Matveev — Cand. Sci. (Econ.), Assoc. Prof., Department of Accounting</p><p>Nizhny Novgorod</p></bio><email xlink:type="simple">super.vma@yandex.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Нижегородский государственный университет им. Н.И. Лобачевского</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Lobachevsky State University of Nizhny Novgorod</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>24</day><month>08</month><year>2021</year></pub-date><volume>25</volume><issue>4</issue><fpage>136</fpage><lpage>151</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Овчаров А.О., Матвеев В.А., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Овчаров А.О., Матвеев В.А.</copyright-holder><copyright-holder xml:lang="en">Ovcharov A.О., Matveev V.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://financetp.fa.ru/jour/article/view/1283">https://financetp.fa.ru/jour/article/view/1283</self-uri><abstract><p>Актуальность темы исследования диктуется возрастающей ролью нетрадиционных финансовых инструментов, которые вносят свой вклад в уровень финансовой нестабильности. Поэтому необходимы разнообразные индикаторы, позволяющие отображать ситуацию на рынке цифровых финансовых активов, волатильность котировок и уровень доверия инвесторов. Цель исследования — разработка и апробация на эмпирических данных обобщающего индикатора финансовой нестабильности (индекса финансового страха) на рынке цифровых финансовых активов. Новизна исследования заключается в адаптации классической модели построения индекса волатильности к рынку криптовалют. В работе использованы статистические методы сбора и обработки данных, анализа временных рядов, взвешивания, конструирования экономических показателей. Обобщены результаты современных исследований по взаимосвязи цифровизации и финансовой нестабильности. Сделан вывод, что в определенные непродолжительные периоды 2020 г. волатильность рубля к доллару была сопоставима или даже выше, чем к биткоину. Кроме того, на самом криптовалютном рынке сегодня намного меньше страха и неопределенности, чем было в конце 2018 г. Главный результат исследования — модель индекса финансового страха, основанная на применении метода расчета средневзвешенной опционной цены базисного актива и хеджирования ценовых рисков. Тестирование модели осуществлено по данным о заявочных ценах на покупку, продажу криптовалюты на определенный момент времени. Получены оценки, свидетельствующие о нарастании нестабильности на рынке цифровых финансовых активов. Сформулированы рекомендации в отношении пороговых значений индекса, по которым можно определить уровень страха инвесторов.</p></abstract><trans-abstract xml:lang="en"><p>The relevance of the research topic is due to the increasing role of non-traditional financial instruments that contribute to financial instability. Therefore, various indicators are required to reflect the situation in the digital financial assets market, the volatility quotes, and the level of investor confidence. The aim of the study is to develop and test on empirical data a generalized indicator of financial instability (financial fear index) in the digital financial assets market. The novelty of the research lies in the adaptation of the classic model of building the volatility index to the cryptocurrency market.The authors use statistical methods for collecting and processing data, analyzing time series, weighing, designing economic indicators. The paper summarizes the results of modern research on the correlation between digitalization and financial instability. The authors conclude that at certain short periods of 2020 the ruble-dollar volatility was comparable or even higher than the ruble-bitcoin one. In addition, there is much less fear and uncertainty in the cryptocurrency market today than there was at the end of 2018. The main result of the study is the financial fear index model based on the method of calculating the weighted average option price of the underlying asset and hedging of price risks. The model has been tested using data on the bid and ask prices of cryptocurrencies at a specific point in time. Estimates have been obtained indicating the growing instability in the digital financial asset market. The authors offer recommendations regarding the index threshold values, which indicate the level of investors’ fear.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>индекс страха</kwd><kwd>цифровые финансовые активы</kwd><kwd>криптовалютный рынок</kwd><kwd>волатильность</kwd><kwd>финансовая нестабильность</kwd><kwd>опционные контракты</kwd></kwd-group><kwd-group xml:lang="en"><kwd>G01</kwd><kwd>C58</kwd><kwd>E44</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Исследование выполнено при финансовой поддержке РФФИ в рамках научного проекта № 19-01000716. Нижегородский государственный университет им. Н. И. Лобачевского, Нижний Новгород, Россия</funding-statement><funding-statement xml:lang="en">The reported study was funded by RFBR according to the research project No. 19-010-00716. Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russia.</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Trelewicz J.Q. Big data and big money: The role of data in the financial sector. IT Professional. 2017;19(3):810. DOI: 10.1109/MITP.2017.45</mixed-citation><mixed-citation xml:lang="en">Trelewicz J.Q. Big data and big money: The role of data in the fi	sector. IT Professional. 2017;19(3):8-10. DOI: 10.1109/MITP.2017.45</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Булгаков А.Л. Big Data в финансах. 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